{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import json\n",
    "import os\n",
    "import warnings\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import glob\n",
    "import matplotlib.pyplot as plt\n",
    "from nltk.corpus import stopwords\n",
    "import re\n",
    "import string\n",
    "from wordcloud import WordCloud, STOPWORDS\n",
    "import seaborn as sns\n",
    "warnings.filterwarnings(\"ignore\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "outputs": [],
   "source": [
    "all_dir = os.listdir(\"kaggle/input/coleridgeinitiative-show-us-the-data\")\n",
    "# train_path = \"kaggle/input/coleridgeinitiative-show-us-the-data/train\"\n",
    "test_path = \"kaggle/input/coleridgeinitiative-show-us-the-data/train\"\n",
    "sub_path = \"kaggle/input/coleridgeinitiative-show-us-the-data/sample_submission.csv\"\n",
    "train_path = \"kaggle/input/coleridgeinitiative-show-us-the-data/train.csv\""
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "outputs": [
    {
     "data": {
      "text/plain": "                                     Id  \\\n0  d0fa7568-7d8e-4db9-870f-f9c6f668c17b   \n1  2f26f645-3dec-485d-b68d-f013c9e05e60   \n2  c5d5cd2c-59de-4f29-bbb1-6a88c7b52f29   \n3  5c9a3bc9-41ba-4574-ad71-e25c1442c8af   \n4  c754dec7-c5a3-4337-9892-c02158475064   \n\n                                           pub_title  \\\n0  The Impact of Dual Enrollment on College Degre...   \n1  Educational Attainment of High School Dropouts...   \n2  Differences in Outcomes for Female and Male St...   \n3  Stepping Stone and Option Value in a Model of ...   \n4  Parental Effort, School Resources, and Student...   \n\n                           dataset_title  \\\n0  National Education Longitudinal Study   \n1  National Education Longitudinal Study   \n2  National Education Longitudinal Study   \n3  National Education Longitudinal Study   \n4  National Education Longitudinal Study   \n\n                           dataset_label  \\\n0  National Education Longitudinal Study   \n1  National Education Longitudinal Study   \n2  National Education Longitudinal Study   \n3  National Education Longitudinal Study   \n4  National Education Longitudinal Study   \n\n                           cleaned_label  \n0  national education longitudinal study  \n1  national education longitudinal study  \n2  national education longitudinal study  \n3  national education longitudinal study  \n4  national education longitudinal study  ",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Id</th>\n      <th>pub_title</th>\n      <th>dataset_title</th>\n      <th>dataset_label</th>\n      <th>cleaned_label</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>d0fa7568-7d8e-4db9-870f-f9c6f668c17b</td>\n      <td>The Impact of Dual Enrollment on College Degre...</td>\n      <td>National Education Longitudinal Study</td>\n      <td>National Education Longitudinal Study</td>\n      <td>national education longitudinal study</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2f26f645-3dec-485d-b68d-f013c9e05e60</td>\n      <td>Educational Attainment of High School Dropouts...</td>\n      <td>National Education Longitudinal Study</td>\n      <td>National Education Longitudinal Study</td>\n      <td>national education longitudinal study</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>c5d5cd2c-59de-4f29-bbb1-6a88c7b52f29</td>\n      <td>Differences in Outcomes for Female and Male St...</td>\n      <td>National Education Longitudinal Study</td>\n      <td>National Education Longitudinal Study</td>\n      <td>national education longitudinal study</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>5c9a3bc9-41ba-4574-ad71-e25c1442c8af</td>\n      <td>Stepping Stone and Option Value in a Model of ...</td>\n      <td>National Education Longitudinal Study</td>\n      <td>National Education Longitudinal Study</td>\n      <td>national education longitudinal study</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>c754dec7-c5a3-4337-9892-c02158475064</td>\n      <td>Parental Effort, School Resources, and Student...</td>\n      <td>National Education Longitudinal Study</td>\n      <td>National Education Longitudinal Study</td>\n      <td>national education longitudinal study</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# train.csv中的内容，有5个字段\n",
    "train_df = pd.read_csv(train_path)  # reading csv file\n",
    "train_df.head(5) # get the first 5 rows"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "文章段落长度：20\n",
      "[{'section_title': 'Abstract', 'text': \"The aim of this study was to identify if acquiring ICT skills through DOT Lebanon's ICT training program (a local NGO) improved income generation opportunities after 3-months of completing the training. The target population was the NGO's vulnerable young beneficiaries. This study was completed in an effort to find creative and digital solutions to the high rate of youth unemployment in Lebanon (37%), one of the highest rates in the world. Results showed that 48% of beneficiaries who were unemployed at baseline, were exposed to at least one income generation opportunity 3 months after completing the DOT Lebanon training. Also, 49% of beneficiaries who were already employed at baseline were exposed to at least one income generation opportunity. Gender, English proficiency and governorate were variables that were found to be statistically significant. Males were more likely than females to be exposed to income generation opportunities. Those who knew little English had better chances than those who had no English proficiency. Beneficiaries living in the capital Beirut were more likely than others to be exposed to income generation opportunities.\"}]\n",
      "子标题: Abstract\n",
      "内容: The aim of this study was to identify if acquiring ICT skills through DOT Lebanon's ICT training program (a local NGO) improved income generation opportunities after 3-months of completing the training. The target population was the NGO's vulnerable young beneficiaries. This study was completed in an effort to find creative and digital solutions to the high rate of youth unemployment in Lebanon (37%), one of the highest rates in the world. Results showed that 48% of beneficiaries who were unemployed at baseline, were exposed to at least one income generation opportunity 3 months after completing the DOT Lebanon training. Also, 49% of beneficiaries who were already employed at baseline were exposed to at least one income generation opportunity. Gender, English proficiency and governorate were variables that were found to be statistically significant. Males were more likely than females to be exposed to income generation opportunities. Those who knew little English had better chances than those who had no English proficiency. Beneficiaries living in the capital Beirut were more likely than others to be exposed to income generation opportunities.\n"
     ]
    }
   ],
   "source": [
    "# Id可以关联一篇文章\n",
    "with open(\"kaggle/input/coleridgeinitiative-show-us-the-data/train/0007f880-0a9b-492d-9a58-76eb0b0e0bd7.json\") as f:\n",
    "    sample = json.load(f)\n",
    "print(\"文章段落长度：\"+ str(len(sample)))\n",
    "# 第一段子标题和内容\n",
    "print(sample[:1])\n",
    "print(\"子标题: \" + sample[0]['section_title'])\n",
    "print(\"内容: \" + sample[0]['text'])\n"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "outputs": [
    {
     "data": {
      "text/plain": "                                         Id  \\\n14795  170113f9-399c-489e-ab53-2faf5c64c5bc   \n14796  170113f9-399c-489e-ab53-2faf5c64c5bc   \n14797  170113f9-399c-489e-ab53-2faf5c64c5bc   \n14798  170113f9-399c-489e-ab53-2faf5c64c5bc   \n14802  170113f9-399c-489e-ab53-2faf5c64c5bc   \n14803  170113f9-399c-489e-ab53-2faf5c64c5bc   \n14804  170113f9-399c-489e-ab53-2faf5c64c5bc   \n14805  170113f9-399c-489e-ab53-2faf5c64c5bc   \n14809  170113f9-399c-489e-ab53-2faf5c64c5bc   \n14810  170113f9-399c-489e-ab53-2faf5c64c5bc   \n14814  170113f9-399c-489e-ab53-2faf5c64c5bc   \n14816  170113f9-399c-489e-ab53-2faf5c64c5bc   \n\n                                     pub_title  \\\n14795  Science and Engineering Indicators 2014   \n14796  Science and Engineering Indicators 2014   \n14797  Science and Engineering Indicators 2014   \n14798  Science and Engineering Indicators 2014   \n14802  Science and Engineering Indicators 2014   \n14803  Science and Engineering Indicators 2014   \n14804  Science and Engineering Indicators 2014   \n14805  Science and Engineering Indicators 2014   \n14809  Science and Engineering Indicators 2014   \n14810  Science and Engineering Indicators 2014   \n14814  Science and Engineering Indicators 2014   \n14816  Science and Engineering Indicators 2014   \n\n                                           dataset_title  \\\n14795                    Beginning Postsecondary Student   \n14796  Survey of Science and Engineering Research Fac...   \n14797   Higher Education Research and Development Survey   \n14798                        Survey of Earned Doctorates   \n14802                     Survey of Doctorate Recipients   \n14803  Survey of Graduate Students and Postdoctorates...   \n14804                       Education Longitudinal Study   \n14805                 Early Childhood Longitudinal Study   \n14809  Trends in International Mathematics and Scienc...   \n14810      Survey of Industrial Research and Development   \n14814              National Education Longitudinal Study   \n14816                     High School Longitudinal Study   \n\n                                           dataset_label  \\\n14795  Beginning Postsecondary Students Longitudinal ...   \n14796  National Science Foundation Survey of Science ...   \n14797  National Science Foundation Higher Education R...   \n14798                        Survey of Earned Doctorates   \n14802                     Survey of Doctorate Recipients   \n14803  Survey of Graduate Students and Postdoctorates...   \n14804                       Education Longitudinal Study   \n14805                 Early Childhood Longitudinal Study   \n14809  Trends in International Mathematics and Scienc...   \n14810  National Center for Science and Engineering St...   \n14814              National Education Longitudinal Study   \n14816                     High School Longitudinal Study   \n\n                                           cleaned_label  \n14795  beginning postsecondary students longitudinal ...  \n14796  national science foundation survey of science ...  \n14797  national science foundation higher education r...  \n14798                        survey of earned doctorates  \n14802                     survey of doctorate recipients  \n14803  survey of graduate students and postdoctorates...  \n14804                       education longitudinal study  \n14805                 early childhood longitudinal study  \n14809  trends in international mathematics and scienc...  \n14810  national center for science and engineering st...  \n14814              national education longitudinal study  \n14816                     high school longitudinal study  ",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Id</th>\n      <th>pub_title</th>\n      <th>dataset_title</th>\n      <th>dataset_label</th>\n      <th>cleaned_label</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>14795</th>\n      <td>170113f9-399c-489e-ab53-2faf5c64c5bc</td>\n      <td>Science and Engineering Indicators 2014</td>\n      <td>Beginning Postsecondary Student</td>\n      <td>Beginning Postsecondary Students Longitudinal ...</td>\n      <td>beginning postsecondary students longitudinal ...</td>\n    </tr>\n    <tr>\n      <th>14796</th>\n      <td>170113f9-399c-489e-ab53-2faf5c64c5bc</td>\n      <td>Science and Engineering Indicators 2014</td>\n      <td>Survey of Science and Engineering Research Fac...</td>\n      <td>National Science Foundation Survey of Science ...</td>\n      <td>national science foundation survey of science ...</td>\n    </tr>\n    <tr>\n      <th>14797</th>\n      <td>170113f9-399c-489e-ab53-2faf5c64c5bc</td>\n      <td>Science and Engineering Indicators 2014</td>\n      <td>Higher Education Research and Development Survey</td>\n      <td>National Science Foundation Higher Education R...</td>\n      <td>national science foundation higher education r...</td>\n    </tr>\n    <tr>\n      <th>14798</th>\n      <td>170113f9-399c-489e-ab53-2faf5c64c5bc</td>\n      <td>Science and Engineering Indicators 2014</td>\n      <td>Survey of Earned Doctorates</td>\n      <td>Survey of Earned Doctorates</td>\n      <td>survey of earned doctorates</td>\n    </tr>\n    <tr>\n      <th>14802</th>\n      <td>170113f9-399c-489e-ab53-2faf5c64c5bc</td>\n      <td>Science and Engineering Indicators 2014</td>\n      <td>Survey of Doctorate Recipients</td>\n      <td>Survey of Doctorate Recipients</td>\n      <td>survey of doctorate recipients</td>\n    </tr>\n    <tr>\n      <th>14803</th>\n      <td>170113f9-399c-489e-ab53-2faf5c64c5bc</td>\n      <td>Science and Engineering Indicators 2014</td>\n      <td>Survey of Graduate Students and Postdoctorates...</td>\n      <td>Survey of Graduate Students and Postdoctorates...</td>\n      <td>survey of graduate students and postdoctorates...</td>\n    </tr>\n    <tr>\n      <th>14804</th>\n      <td>170113f9-399c-489e-ab53-2faf5c64c5bc</td>\n      <td>Science and Engineering Indicators 2014</td>\n      <td>Education Longitudinal Study</td>\n      <td>Education Longitudinal Study</td>\n      <td>education longitudinal study</td>\n    </tr>\n    <tr>\n      <th>14805</th>\n      <td>170113f9-399c-489e-ab53-2faf5c64c5bc</td>\n      <td>Science and Engineering Indicators 2014</td>\n      <td>Early Childhood Longitudinal Study</td>\n      <td>Early Childhood Longitudinal Study</td>\n      <td>early childhood longitudinal study</td>\n    </tr>\n    <tr>\n      <th>14809</th>\n      <td>170113f9-399c-489e-ab53-2faf5c64c5bc</td>\n      <td>Science and Engineering Indicators 2014</td>\n      <td>Trends in International Mathematics and Scienc...</td>\n      <td>Trends in International Mathematics and Scienc...</td>\n      <td>trends in international mathematics and scienc...</td>\n    </tr>\n    <tr>\n      <th>14810</th>\n      <td>170113f9-399c-489e-ab53-2faf5c64c5bc</td>\n      <td>Science and Engineering Indicators 2014</td>\n      <td>Survey of Industrial Research and Development</td>\n      <td>National Center for Science and Engineering St...</td>\n      <td>national center for science and engineering st...</td>\n    </tr>\n    <tr>\n      <th>14814</th>\n      <td>170113f9-399c-489e-ab53-2faf5c64c5bc</td>\n      <td>Science and Engineering Indicators 2014</td>\n      <td>National Education Longitudinal Study</td>\n      <td>National Education Longitudinal Study</td>\n      <td>national education longitudinal study</td>\n    </tr>\n    <tr>\n      <th>14816</th>\n      <td>170113f9-399c-489e-ab53-2faf5c64c5bc</td>\n      <td>Science and Engineering Indicators 2014</td>\n      <td>High School Longitudinal Study</td>\n      <td>High School Longitudinal Study</td>\n      <td>high school longitudinal study</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 一篇文章里可能会对应多个数据集\n",
    "duplicate_df = train_df[train_df['Id'] == \"170113f9-399c-489e-ab53-2faf5c64c5bc\"].drop_duplicates(\"dataset_title\")\n",
    "duplicate_df"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "outputs": [
    {
     "data": {
      "text/plain": "                                          Id  \\\ncount                                  19661   \nunique                                 14316   \ntop     170113f9-399c-489e-ab53-2faf5c64c5bc   \nfreq                                      22   \n\n                                      pub_title  \\\ncount                                     19661   \nunique                                    14271   \ntop     Science and Engineering Indicators 2014   \nfreq                                         22   \n\n                                            dataset_title dataset_label  \\\ncount                                               19661         19661   \nunique                                                 45           130   \ntop     Alzheimer's Disease Neuroimaging Initiative (A...          ADNI   \nfreq                                                 6144          3673   \n\n       cleaned_label  \ncount          19661  \nunique           130  \ntop             adni  \nfreq            3673  ",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Id</th>\n      <th>pub_title</th>\n      <th>dataset_title</th>\n      <th>dataset_label</th>\n      <th>cleaned_label</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>count</th>\n      <td>19661</td>\n      <td>19661</td>\n      <td>19661</td>\n      <td>19661</td>\n      <td>19661</td>\n    </tr>\n    <tr>\n      <th>unique</th>\n      <td>14316</td>\n      <td>14271</td>\n      <td>45</td>\n      <td>130</td>\n      <td>130</td>\n    </tr>\n    <tr>\n      <th>top</th>\n      <td>170113f9-399c-489e-ab53-2faf5c64c5bc</td>\n      <td>Science and Engineering Indicators 2014</td>\n      <td>Alzheimer's Disease Neuroimaging Initiative (A...</td>\n      <td>ADNI</td>\n      <td>adni</td>\n    </tr>\n    <tr>\n      <th>freq</th>\n      <td>22</td>\n      <td>22</td>\n      <td>6144</td>\n      <td>3673</td>\n      <td>3673</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 一共14316个id，14271篇文章，45个dataset_title，但是label有130个\n",
    "# 其中Science and Engineering Indicators 2014包含的数据集最多，有22个\n",
    "# ADNI出现了最多次，但是其dataset_title是它的全称，label需要提取它的缩写\n",
    "train_df.describe()\n"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "outputs": [],
   "source": [
    "# 检查一下具有不同数据集标签的Id\n",
    "dataset_title = train_df.groupby('Id').count()[['dataset_title']].sort_values(by = \"dataset_title\", ascending = False)\n",
    "id_pub_title = dataset_title[dataset_title['dataset_title'] >1][['dataset_title']].reset_index()"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "outputs": [
    {
     "data": {
      "text/plain": "Text(0.5, 0, 'Count')"
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 936x936 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 每篇文章包含数据集的个数\n",
    "plt.figure(figsize = (13,13))\n",
    "sns.barplot(id_pub_title['dataset_title'].iloc[:20], id_pub_title['Id'].iloc[:20])\n",
    "plt.title(\"每篇文章包含数据集的个数\")\n",
    "plt.xticks(fontsize=13)\n",
    "plt.yticks(fontsize=13)\n",
    "plt.ylabel(\"\")\n",
    "plt.xlabel(\"Count\", fontsize=14)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "outputs": [
    {
     "data": {
      "text/plain": "                                               pub_title  dataset_title\n0                Science and Engineering Indicators 2014             22\n1       Digest of Education Statistics, 2012 NCES 201...             12\n2                Science and Engineering Indicators 2008             12\n3                Science and Engineering Indicators 2010             11\n4      Programs and Plans of the National Center for ...             10\n...                                                  ...            ...\n14266  Inherent Structure-Guided Multi-view Learning ...              1\n14267  Inhibitors of SARS-CoV-2 Entry: Current and Fu...              1\n14268  Initial Public Health Response and Interim Cli...              1\n14269  Initial rapid and proactive response for the C...              1\n14270  “You are our eyes and ears”: A new tool for ob...              1\n\n[14271 rows x 2 columns]",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>pub_title</th>\n      <th>dataset_title</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>Science and Engineering Indicators 2014</td>\n      <td>22</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>Digest of Education Statistics, 2012 NCES 201...</td>\n      <td>12</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>Science and Engineering Indicators 2008</td>\n      <td>12</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>Science and Engineering Indicators 2010</td>\n      <td>11</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>Programs and Plans of the National Center for ...</td>\n      <td>10</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>14266</th>\n      <td>Inherent Structure-Guided Multi-view Learning ...</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>14267</th>\n      <td>Inhibitors of SARS-CoV-2 Entry: Current and Fu...</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>14268</th>\n      <td>Initial Public Health Response and Interim Cli...</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>14269</th>\n      <td>Initial rapid and proactive response for the C...</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>14270</th>\n      <td>“You are our eyes and ears”: A new tool for ob...</td>\n      <td>1</td>\n    </tr>\n  </tbody>\n</table>\n<p>14271 rows × 2 columns</p>\n</div>"
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 每篇文章包含数据集的个数\n",
    "pub_title = train_df.groupby('pub_title').count()[['dataset_title']].sort_values(by = ['dataset_title'], ascending = False)\n",
    "id_title = pub_title.reset_index()\n",
    "id_title"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "outputs": [
    {
     "data": {
      "text/plain": "                                         Id  \\\n4973   375892cf-e69b-4fc2-b4e6-2f735fa572aa   \n11630  3a00beee-3121-4a85-bdf4-545fc630cce5   \n14215  0b4eb736-abe8-45b8-8ee7-6fbfe4431a6b   \n4505   48c64db8-2abf-49cb-8107-460dcb0de8c3   \n16586  7f176955-8aee-4a89-86fd-0df053468bbb   \n...                                     ...   \n18252  4e669f3d-a53e-4db8-ace9-03376076f9d6   \n5815   e5667ac5-dad6-4474-9676-400e4acd6a97   \n8929   93e3eb41-eeb7-41fe-83f4-a62247a4a974   \n1803   1d960f41-f0f6-4e25-9774-68e91b44e78a   \n10543  81f36b9a-f919-4f40-964c-7a6d0fea8fea   \n\n                                               pub_title  \\\n4973   Neural Dynamics during Resting State: A Functi...   \n11630  THE IMPACT OF INFORMATION TECHNOLOGY ON SCIENT...   \n14215   Development of a performance-based design app...   \n4505   Tackling Multiple Ordinal Regression Problems:...   \n16586  Does Postsecondary Persistence in STEM Vary by...   \n...                                                  ...   \n18252  Monitoring the biodiversity of regions: Key pr...   \n5815   Effect of sample size re-estimation in adaptiv...   \n8929   A Novel Method to Estimate Long‐Term Chronolog...   \n1803   Exercise-induced premature ventricular beats: ...   \n10543  Modulation of glucose metabolism and metabolic...   \n\n                                           dataset_title  \\\n4973   Alzheimer's Disease Neuroimaging Initiative (A...   \n11630                     Survey of Doctorate Recipients   \n14215     Sea, Lake, and Overland Surges from Hurricanes   \n4505   Alzheimer's Disease Neuroimaging Initiative (A...   \n16586                    Beginning Postsecondary Student   \n...                                                  ...   \n18252          North American Breeding Bird Survey (BBS)   \n5815   Alzheimer's Disease Neuroimaging Initiative (A...   \n8929   Alzheimer's Disease Neuroimaging Initiative (A...   \n1803        Baltimore Longitudinal Study of Aging (BLSA)   \n10543  Alzheimer's Disease Neuroimaging Initiative (A...   \n\n                                           dataset_label  \\\n4973                                                ADNI   \n11630                     Survey of Doctorate Recipients   \n14215                                        SLOSH model   \n4505                                                ADNI   \n16586                   Beginning Postsecondary Students   \n...                                                  ...   \n18252                North American Breeding Bird Survey   \n5815                                                ADNI   \n8929   Alzheimer's Disease Neuroimaging Initiative (A...   \n1803               Baltimore Longitudinal Study of Aging   \n10543  Alzheimer's Disease Neuroimaging Initiative (A...   \n\n                                           cleaned_label  \n4973                                                adni  \n11630                     survey of doctorate recipients  \n14215                                        slosh model  \n4505                                                adni  \n16586                   beginning postsecondary students  \n...                                                  ...  \n18252                north american breeding bird survey  \n5815                                                adni  \n8929   alzheimer s disease neuroimaging initiative adni   \n1803               baltimore longitudinal study of aging  \n10543  alzheimer s disease neuroimaging initiative adni   \n\n[100 rows x 5 columns]",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Id</th>\n      <th>pub_title</th>\n      <th>dataset_title</th>\n      <th>dataset_label</th>\n      <th>cleaned_label</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>4973</th>\n      <td>375892cf-e69b-4fc2-b4e6-2f735fa572aa</td>\n      <td>Neural Dynamics during Resting State: A Functi...</td>\n      <td>Alzheimer's Disease Neuroimaging Initiative (A...</td>\n      <td>ADNI</td>\n      <td>adni</td>\n    </tr>\n    <tr>\n      <th>11630</th>\n      <td>3a00beee-3121-4a85-bdf4-545fc630cce5</td>\n      <td>THE IMPACT OF INFORMATION TECHNOLOGY ON SCIENT...</td>\n      <td>Survey of Doctorate Recipients</td>\n      <td>Survey of Doctorate Recipients</td>\n      <td>survey of doctorate recipients</td>\n    </tr>\n    <tr>\n      <th>14215</th>\n      <td>0b4eb736-abe8-45b8-8ee7-6fbfe4431a6b</td>\n      <td>Development of a performance-based design app...</td>\n      <td>Sea, Lake, and Overland Surges from Hurricanes</td>\n      <td>SLOSH model</td>\n      <td>slosh model</td>\n    </tr>\n    <tr>\n      <th>4505</th>\n      <td>48c64db8-2abf-49cb-8107-460dcb0de8c3</td>\n      <td>Tackling Multiple Ordinal Regression Problems:...</td>\n      <td>Alzheimer's Disease Neuroimaging Initiative (A...</td>\n      <td>ADNI</td>\n      <td>adni</td>\n    </tr>\n    <tr>\n      <th>16586</th>\n      <td>7f176955-8aee-4a89-86fd-0df053468bbb</td>\n      <td>Does Postsecondary Persistence in STEM Vary by...</td>\n      <td>Beginning Postsecondary Student</td>\n      <td>Beginning Postsecondary Students</td>\n      <td>beginning postsecondary students</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>18252</th>\n      <td>4e669f3d-a53e-4db8-ace9-03376076f9d6</td>\n      <td>Monitoring the biodiversity of regions: Key pr...</td>\n      <td>North American Breeding Bird Survey (BBS)</td>\n      <td>North American Breeding Bird Survey</td>\n      <td>north american breeding bird survey</td>\n    </tr>\n    <tr>\n      <th>5815</th>\n      <td>e5667ac5-dad6-4474-9676-400e4acd6a97</td>\n      <td>Effect of sample size re-estimation in adaptiv...</td>\n      <td>Alzheimer's Disease Neuroimaging Initiative (A...</td>\n      <td>ADNI</td>\n      <td>adni</td>\n    </tr>\n    <tr>\n      <th>8929</th>\n      <td>93e3eb41-eeb7-41fe-83f4-a62247a4a974</td>\n      <td>A Novel Method to Estimate Long‐Term Chronolog...</td>\n      <td>Alzheimer's Disease Neuroimaging Initiative (A...</td>\n      <td>Alzheimer's Disease Neuroimaging Initiative (A...</td>\n      <td>alzheimer s disease neuroimaging initiative adni</td>\n    </tr>\n    <tr>\n      <th>1803</th>\n      <td>1d960f41-f0f6-4e25-9774-68e91b44e78a</td>\n      <td>Exercise-induced premature ventricular beats: ...</td>\n      <td>Baltimore Longitudinal Study of Aging (BLSA)</td>\n      <td>Baltimore Longitudinal Study of Aging</td>\n      <td>baltimore longitudinal study of aging</td>\n    </tr>\n    <tr>\n      <th>10543</th>\n      <td>81f36b9a-f919-4f40-964c-7a6d0fea8fea</td>\n      <td>Modulation of glucose metabolism and metabolic...</td>\n      <td>Alzheimer's Disease Neuroimaging Initiative (A...</td>\n      <td>Alzheimer's Disease Neuroimaging Initiative (A...</td>\n      <td>alzheimer s disease neuroimaging initiative adni</td>\n    </tr>\n  </tbody>\n</table>\n<p>100 rows × 5 columns</p>\n</div>"
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 为了加快处理速度，先随机选100个样本\n",
    "train_df = train_df.sample(100)\n",
    "train_df"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 864x864 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 词云\n",
    "stopwords = set(STOPWORDS)\n",
    "wordcloud = WordCloud(background_color='white',\n",
    "                      stopwords=stopwords,\n",
    "                      max_words=100,\n",
    "                      max_font_size=30,\n",
    "                      scale=3,\n",
    "                      random_state=1)\n",
    "\n",
    "wordcloud=wordcloud.generate(str(train_df['dataset_title'].unique()))\n",
    "fig = plt.figure(1, figsize=(12, 12))\n",
    "plt.axis('off')\n",
    "plt.imshow(wordcloud)\n",
    "plt.show()"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "outputs": [],
   "source": [
    "# 现在让我们将json文件中的文本与我们的训练csv文件连接起来\n",
    "def get_text(filename, test=False):\n",
    "    if test:\n",
    "        df = pd.read_json('kaggle/input/coleridgeinitiative-show-us-the-data/test/{}.json'.format(filename))\n",
    "    else:\n",
    "        df = pd.read_json('kaggle/input/coleridgeinitiative-show-us-the-data/train/{}.json'.format(filename))\n",
    "    text = \" \".join(list(df['text']))\n",
    "    return text\n",
    "\n",
    "def get_paragraph_len(filename, test=False):\n",
    "    if test:\n",
    "        df = pd.read_json('kaggle/input/coleridgeinitiative-show-us-the-data/test/{}.json'.format(filename))\n",
    "    else:\n",
    "        df = pd.read_json('kaggle/input/coleridgeinitiative-show-us-the-data/train/{}.json'.format(filename))\n",
    "    len_ = len(list(df['text']))\n",
    "    return len_"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "outputs": [
    {
     "data": {
      "text/plain": "                                         Id  \\\n4973   375892cf-e69b-4fc2-b4e6-2f735fa572aa   \n10225  9c10b7f2-ffde-493a-bd31-232be541c3a1   \n2026   4fc1c61b-aaad-473c-8184-0b7c60c324eb   \n6524   45cf38af-717b-446f-9bf8-346f1955595b   \n3622   b0a52ec8-8cf4-4702-b651-afd0abe9015c   \n\n                                               pub_title  \\\n4973   Neural Dynamics during Resting State: A Functi...   \n10225  A Multi-Marker Genetic Association Test Based ...   \n2026   Normal Hearing Ability but Impaired Auditory S...   \n6524   Joint feature-sample selection and robust diag...   \n3622   Resting State BOLD Variability in Alzheimer’s ...   \n\n                                           dataset_title  \\\n4973   Alzheimer's Disease Neuroimaging Initiative (A...   \n10225  Alzheimer's Disease Neuroimaging Initiative (A...   \n2026        Baltimore Longitudinal Study of Aging (BLSA)   \n6524   Alzheimer's Disease Neuroimaging Initiative (A...   \n3622   Alzheimer's Disease Neuroimaging Initiative (A...   \n\n                                           dataset_label  \\\n4973                                                ADNI   \n10225  Alzheimer's Disease Neuroimaging Initiative (A...   \n2026               Baltimore Longitudinal Study of Aging   \n6524                                                ADNI   \n3622                                                ADNI   \n\n                                           cleaned_label  \\\n4973                                                adni   \n10225  alzheimer s disease neuroimaging initiative adni    \n2026               baltimore longitudinal study of aging   \n6524                                                adni   \n3622                                                adni   \n\n                                                    text  paragraph_len  \n4973   The brain is a complex high-order system. Body...             15  \n10225  Results from Genome-Wide Association Studies (...             11  \n2026   Patients with Alzheimer's disease (AD) often r...             23  \n6524   Parkinson's disease (PD) is an overwhelming ne...             21  \n3622   Background: Alzheimer's disease (AD) is a neur...             26  ",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Id</th>\n      <th>pub_title</th>\n      <th>dataset_title</th>\n      <th>dataset_label</th>\n      <th>cleaned_label</th>\n      <th>text</th>\n      <th>paragraph_len</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>4973</th>\n      <td>375892cf-e69b-4fc2-b4e6-2f735fa572aa</td>\n      <td>Neural Dynamics during Resting State: A Functi...</td>\n      <td>Alzheimer's Disease Neuroimaging Initiative (A...</td>\n      <td>ADNI</td>\n      <td>adni</td>\n      <td>The brain is a complex high-order system. Body...</td>\n      <td>15</td>\n    </tr>\n    <tr>\n      <th>10225</th>\n      <td>9c10b7f2-ffde-493a-bd31-232be541c3a1</td>\n      <td>A Multi-Marker Genetic Association Test Based ...</td>\n      <td>Alzheimer's Disease Neuroimaging Initiative (A...</td>\n      <td>Alzheimer's Disease Neuroimaging Initiative (A...</td>\n      <td>alzheimer s disease neuroimaging initiative adni</td>\n      <td>Results from Genome-Wide Association Studies (...</td>\n      <td>11</td>\n    </tr>\n    <tr>\n      <th>2026</th>\n      <td>4fc1c61b-aaad-473c-8184-0b7c60c324eb</td>\n      <td>Normal Hearing Ability but Impaired Auditory S...</td>\n      <td>Baltimore Longitudinal Study of Aging (BLSA)</td>\n      <td>Baltimore Longitudinal Study of Aging</td>\n      <td>baltimore longitudinal study of aging</td>\n      <td>Patients with Alzheimer's disease (AD) often r...</td>\n      <td>23</td>\n    </tr>\n    <tr>\n      <th>6524</th>\n      <td>45cf38af-717b-446f-9bf8-346f1955595b</td>\n      <td>Joint feature-sample selection and robust diag...</td>\n      <td>Alzheimer's Disease Neuroimaging Initiative (A...</td>\n      <td>ADNI</td>\n      <td>adni</td>\n      <td>Parkinson's disease (PD) is an overwhelming ne...</td>\n      <td>21</td>\n    </tr>\n    <tr>\n      <th>3622</th>\n      <td>b0a52ec8-8cf4-4702-b651-afd0abe9015c</td>\n      <td>Resting State BOLD Variability in Alzheimer’s ...</td>\n      <td>Alzheimer's Disease Neuroimaging Initiative (A...</td>\n      <td>ADNI</td>\n      <td>adni</td>\n      <td>Background: Alzheimer's disease (AD) is a neur...</td>\n      <td>26</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_df['text'] = train_df['Id'].apply(get_text)\n",
    "train_df['paragraph_len'] = train_df['Id'].apply(get_paragraph_len)\n",
    "train_df.sample(5)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "outputs": [
    {
     "data": {
      "text/plain": "                                         Id  \\\n19096  5853156d-567d-4ef6-9315-67ff01c12270   \n14041  a8f044fd-46f9-427e-b094-f1eb2dfc0e55   \n15199  fe4d42a1-96d6-4d93-adc3-0afa4a1bd925   \n11630  3a00beee-3121-4a85-bdf4-545fc630cce5   \n7341   7af886e2-5839-4c65-8641-54152ff6fd19   \n\n                                               pub_title  \\\n19096  Scientific research progress of COVID‐19/SARS‐...   \n14041  School Mobility and Students' Academic and Beh...   \n15199   Marriage and baby blues: Redefining gender eq...   \n11630  THE IMPACT OF INFORMATION TECHNOLOGY ON SCIENT...   \n7341   Survey and Analysis of Computing Education at ...   \n\n                                           dataset_title  \\\n19096                         SARS-CoV-2 genome sequence   \n14041                  School Survey on Crime and Safety   \n15199                        Survey of Earned Doctorates   \n11630                     Survey of Doctorate Recipients   \n7341   Trends in International Mathematics and Scienc...   \n\n                                           dataset_label  \\\n19096                        SARS-CoV-2 genome sequences   \n14041                  School Survey on Crime and Safety   \n15199                        Survey of Earned Doctorates   \n11630                     Survey of Doctorate Recipients   \n7341   Trends in International Mathematics and Scienc...   \n\n                                           cleaned_label  \\\n19096                        sars cov 2 genome sequences   \n14041                  school survey on crime and safety   \n15199                        survey of earned doctorates   \n11630                     survey of doctorate recipients   \n7341   trends in international mathematics and scienc...   \n\n                                                    text  paragraph_len  \\\n19096  In late December 2019, a cluster of pneumonia ...             22   \n14041  Changing schools is a challenge for students a...             14   \n15199  T he traditional approach to issues of gender ...              9   \n11630  This study advances the prior literature conce...             21   \n7341   We conducted the first national survey of comp...             23   \n\n                                                   lower  \n19096  in late december 2019, a cluster of pneumonia ...  \n14041  changing schools is a challenge for students a...  \n15199  t he traditional approach to issues of gender ...  \n11630  this study advances the prior literature conce...  \n7341   we conducted the first national survey of comp...  ",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Id</th>\n      <th>pub_title</th>\n      <th>dataset_title</th>\n      <th>dataset_label</th>\n      <th>cleaned_label</th>\n      <th>text</th>\n      <th>paragraph_len</th>\n      <th>lower</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>19096</th>\n      <td>5853156d-567d-4ef6-9315-67ff01c12270</td>\n      <td>Scientific research progress of COVID‐19/SARS‐...</td>\n      <td>SARS-CoV-2 genome sequence</td>\n      <td>SARS-CoV-2 genome sequences</td>\n      <td>sars cov 2 genome sequences</td>\n      <td>In late December 2019, a cluster of pneumonia ...</td>\n      <td>22</td>\n      <td>in late december 2019, a cluster of pneumonia ...</td>\n    </tr>\n    <tr>\n      <th>14041</th>\n      <td>a8f044fd-46f9-427e-b094-f1eb2dfc0e55</td>\n      <td>School Mobility and Students' Academic and Beh...</td>\n      <td>School Survey on Crime and Safety</td>\n      <td>School Survey on Crime and Safety</td>\n      <td>school survey on crime and safety</td>\n      <td>Changing schools is a challenge for students a...</td>\n      <td>14</td>\n      <td>changing schools is a challenge for students a...</td>\n    </tr>\n    <tr>\n      <th>15199</th>\n      <td>fe4d42a1-96d6-4d93-adc3-0afa4a1bd925</td>\n      <td>Marriage and baby blues: Redefining gender eq...</td>\n      <td>Survey of Earned Doctorates</td>\n      <td>Survey of Earned Doctorates</td>\n      <td>survey of earned doctorates</td>\n      <td>T he traditional approach to issues of gender ...</td>\n      <td>9</td>\n      <td>t he traditional approach to issues of gender ...</td>\n    </tr>\n    <tr>\n      <th>11630</th>\n      <td>3a00beee-3121-4a85-bdf4-545fc630cce5</td>\n      <td>THE IMPACT OF INFORMATION TECHNOLOGY ON SCIENT...</td>\n      <td>Survey of Doctorate Recipients</td>\n      <td>Survey of Doctorate Recipients</td>\n      <td>survey of doctorate recipients</td>\n      <td>This study advances the prior literature conce...</td>\n      <td>21</td>\n      <td>this study advances the prior literature conce...</td>\n    </tr>\n    <tr>\n      <th>7341</th>\n      <td>7af886e2-5839-4c65-8641-54152ff6fd19</td>\n      <td>Survey and Analysis of Computing Education at ...</td>\n      <td>Trends in International Mathematics and Scienc...</td>\n      <td>Trends in International Mathematics and Scienc...</td>\n      <td>trends in international mathematics and scienc...</td>\n      <td>We conducted the first national survey of comp...</td>\n      <td>23</td>\n      <td>we conducted the first national survey of comp...</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# text预处理\n",
    "train_df['lower'] = train_df['text'].str.lower()\n",
    "train_df.sample(5)\n"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "outputs": [
    {
     "data": {
      "text/plain": "                                         Id  \\\n11426  7b096e7e-e86e-4078-b7b9-fe0fecc12bb2   \n4973   375892cf-e69b-4fc2-b4e6-2f735fa572aa   \n4262   e17dee46-d287-492c-9e51-d7026234cd29   \n1803   1d960f41-f0f6-4e25-9774-68e91b44e78a   \n10109  34fb9ed7-ff56-4e9e-b6b2-4e9b97da9314   \n\n                                               pub_title  \\\n11426  Time Series Analysis of Land Cover Change: Dev...   \n4973   Neural Dynamics during Resting State: A Functi...   \n4262   Group sparse reduced rank regression for neuro...   \n1803   Exercise-induced premature ventricular beats: ...   \n10109  Plasma β-amyloid in Alzheimer’s disease and va...   \n\n                                           dataset_title  \\\n11426                    Coastal Change Analysis Program   \n4973   Alzheimer's Disease Neuroimaging Initiative (A...   \n4262   Alzheimer's Disease Neuroimaging Initiative (A...   \n1803        Baltimore Longitudinal Study of Aging (BLSA)   \n10109  Alzheimer's Disease Neuroimaging Initiative (A...   \n\n                                           dataset_label  \\\n11426                    Coastal Change Analysis Program   \n4973                                                ADNI   \n4262                                                ADNI   \n1803               Baltimore Longitudinal Study of Aging   \n10109  Alzheimer's Disease Neuroimaging Initiative (A...   \n\n                                           cleaned_label  \\\n11426                    coastal change analysis program   \n4973                                                adni   \n4262                                                adni   \n1803               baltimore longitudinal study of aging   \n10109  alzheimer s disease neuroimaging initiative adni    \n\n                                                    text  paragraph_len  \\\n11426  Abstract: Despite the existence of long term r...             15   \n4973   The brain is a complex high-order system. Body...             15   \n4262   The neuroimaging genetic study usually needs t...             16   \n1803   xercise testing has typically been used to dia...              2   \n10109  Implementation of amyloid biomarkers in clinic...              8   \n\n                                                   lower  \\\n11426  abstract: despite the existence of long term r...   \n4973   the brain is a complex high-order system. body...   \n4262   the neuroimaging genetic study usually needs t...   \n1803   xercise testing has typically been used to dia...   \n10109  implementation of amyloid biomarkers in clinic...   \n\n                                           text_wo_punct  \n11426  abstract despite the existence of long term re...  \n4973   the brain is a complex highorder system body m...  \n4262   the neuroimaging genetic study usually needs t...  \n1803   xercise testing has typically been used to dia...  \n10109  implementation of amyloid biomarkers in clinic...  ",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Id</th>\n      <th>pub_title</th>\n      <th>dataset_title</th>\n      <th>dataset_label</th>\n      <th>cleaned_label</th>\n      <th>text</th>\n      <th>paragraph_len</th>\n      <th>lower</th>\n      <th>text_wo_punct</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>11426</th>\n      <td>7b096e7e-e86e-4078-b7b9-fe0fecc12bb2</td>\n      <td>Time Series Analysis of Land Cover Change: Dev...</td>\n      <td>Coastal Change Analysis Program</td>\n      <td>Coastal Change Analysis Program</td>\n      <td>coastal change analysis program</td>\n      <td>Abstract: Despite the existence of long term r...</td>\n      <td>15</td>\n      <td>abstract: despite the existence of long term r...</td>\n      <td>abstract despite the existence of long term re...</td>\n    </tr>\n    <tr>\n      <th>4973</th>\n      <td>375892cf-e69b-4fc2-b4e6-2f735fa572aa</td>\n      <td>Neural Dynamics during Resting State: A Functi...</td>\n      <td>Alzheimer's Disease Neuroimaging Initiative (A...</td>\n      <td>ADNI</td>\n      <td>adni</td>\n      <td>The brain is a complex high-order system. Body...</td>\n      <td>15</td>\n      <td>the brain is a complex high-order system. body...</td>\n      <td>the brain is a complex highorder system body m...</td>\n    </tr>\n    <tr>\n      <th>4262</th>\n      <td>e17dee46-d287-492c-9e51-d7026234cd29</td>\n      <td>Group sparse reduced rank regression for neuro...</td>\n      <td>Alzheimer's Disease Neuroimaging Initiative (A...</td>\n      <td>ADNI</td>\n      <td>adni</td>\n      <td>The neuroimaging genetic study usually needs t...</td>\n      <td>16</td>\n      <td>the neuroimaging genetic study usually needs t...</td>\n      <td>the neuroimaging genetic study usually needs t...</td>\n    </tr>\n    <tr>\n      <th>1803</th>\n      <td>1d960f41-f0f6-4e25-9774-68e91b44e78a</td>\n      <td>Exercise-induced premature ventricular beats: ...</td>\n      <td>Baltimore Longitudinal Study of Aging (BLSA)</td>\n      <td>Baltimore Longitudinal Study of Aging</td>\n      <td>baltimore longitudinal study of aging</td>\n      <td>xercise testing has typically been used to dia...</td>\n      <td>2</td>\n      <td>xercise testing has typically been used to dia...</td>\n      <td>xercise testing has typically been used to dia...</td>\n    </tr>\n    <tr>\n      <th>10109</th>\n      <td>34fb9ed7-ff56-4e9e-b6b2-4e9b97da9314</td>\n      <td>Plasma β-amyloid in Alzheimer’s disease and va...</td>\n      <td>Alzheimer's Disease Neuroimaging Initiative (A...</td>\n      <td>Alzheimer's Disease Neuroimaging Initiative (A...</td>\n      <td>alzheimer s disease neuroimaging initiative adni</td>\n      <td>Implementation of amyloid biomarkers in clinic...</td>\n      <td>8</td>\n      <td>implementation of amyloid biomarkers in clinic...</td>\n      <td>implementation of amyloid biomarkers in clinic...</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 删除标点符号\n",
    "\n",
    "# python中的标点符号包含以下标点符号\n",
    "\n",
    "# !\"#$%&\\'()*+,-./:;<=>?@[\\]^_{|}~`\n",
    "\n",
    "PUNCT_TO_REMOVE = '!\"#$%&\\'()*+,-./:;<=>?@[\\\\]^_`{|}~\\n'\n",
    "def remove_punctuation(text):\n",
    "    \"\"\"custom function to remove the punctuation\"\"\"\n",
    "    return text.translate(str.maketrans('', '', PUNCT_TO_REMOVE))\n",
    "\n",
    "# 移除标点\n",
    "train_df[\"text_wo_punct\"] = train_df[\"lower\"].apply(lambda text: remove_punctuation(text))\n",
    "train_df.sample(5)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[nltk_data] Downloading package stopwords to\n",
      "[nltk_data]     C:\\Users\\Administrator\\AppData\\Roaming\\nltk_data...\n",
      "[nltk_data]   Unzipping corpora\\stopwords.zip.\n"
     ]
    },
    {
     "data": {
      "text/plain": "True"
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 停用词\n",
    "from nltk.corpus import stopwords\n",
    "import nltk\n",
    "import ssl\n",
    "\n",
    "try:\n",
    "    _create_unverified_https_context = ssl._create_unverified_context\n",
    "except AttributeError:\n",
    "    pass\n",
    "else:\n",
    "    ssl._create_default_https_context = _create_unverified_https_context\n",
    "\n",
    "nltk.download('stopwords')"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "outputs": [],
   "source": [
    "Stopwords = list(stopwords.words('english'))\n",
    "\n",
    "def remove_stopwords(text):\n",
    "    return \" \".join([word for word in str(text).split() if word not in Stopwords])\n",
    "\n",
    "# 停用词\n",
    "train_df[\"text_wo_stop\"] = train_df[\"text_wo_punct\"].apply(lambda text: remove_stopwords(text))\n",
    "train_df.sample(5)\n",
    "\n",
    "train_df.to_csv('train_df.csv', index = False)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "4973    brain complex highorder system body movements ...\n",
      "Name: text_wo_stop, dtype: object\n",
      "==================================================\n",
      "4973    The brain is a complex high-order system. Body...\n",
      "Name: text, dtype: object\n"
     ]
    }
   ],
   "source": [
    "str1 = train_df['text_wo_stop']\n",
    "str2 = train_df['text']\n",
    "#results\n",
    "print(str1[:1])\n",
    "print(\"=\"* 50)\n",
    "print(str2[:1])"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "outputs": [
    {
     "data": {
      "text/plain": "                                     Id  \\\n0  2100032a-7c33-4bff-97ef-690822c43466   \n1  2f392438-e215-4169-bebf-21ac4ff253e1   \n2  3f316b38-1a24-45a9-8d8c-4e05a42257c6   \n3  8e6996b4-ca08-4c0b-bed2-aaf07a4c6a60   \n\n                                                text  \n0  Cognitive deficits and reduced educational ach...  \n1  This report describes how the education system...  \n2  Cape Hatteras National Seashore (CAHA), locate...  \n3  A significant body of research has been conduc...  ",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Id</th>\n      <th>text</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>2100032a-7c33-4bff-97ef-690822c43466</td>\n      <td>Cognitive deficits and reduced educational ach...</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2f392438-e215-4169-bebf-21ac4ff253e1</td>\n      <td>This report describes how the education system...</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>3f316b38-1a24-45a9-8d8c-4e05a42257c6</td>\n      <td>Cape Hatteras National Seashore (CAHA), locate...</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>8e6996b4-ca08-4c0b-bed2-aaf07a4c6a60</td>\n      <td>A significant body of research has been conduc...</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 获取测试数据的文本\n",
    "test_files = os.listdir('kaggle/input/coleridgeinitiative-show-us-the-data/test')\n",
    "test = pd.DataFrame({'Id':test_files})\n",
    "test['Id'] = test['Id'].apply(lambda x : x.split('.')[0])\n",
    "test['text'] = test['Id'].apply(get_text, test=True)\n",
    "\n",
    "\n",
    "test"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "outputs": [
    {
     "data": {
      "text/plain": "['sars-cov-2 genome sequence',\n 'nces common core of data',\n 'survey of doctorate recipients',\n 'slosh model',\n 'trends in international mathematics and science study',\n 'international best track archive for climate stewardship',\n 'north american breeding bird survey',\n 'noaa optimum interpolation sea surface temperature',\n 'baltimore longitudinal study of aging',\n 'noaa tide gauge',\n 'agricultural resource management survey',\n 'sars-cov-2 genome sequences',\n 'noaa c-cap',\n 'beginning postsecondary students longitudinal study',\n 'common core of data',\n 'census of agriculture',\n 'coastal change analysis program',\n 'baltimore longitudinal study of aging (blsa)',\n 'baccalaureate and beyond longitudinal study',\n 'usgs north american breeding bird survey',\n 'north american breeding bird survey (bbs)',\n 'optimum interpolation sea surface temperature',\n 'adni',\n 'school survey on crime and safety',\n 'high school longitudinal study',\n \"alzheimer's disease neuroimaging initiative (adni)\",\n 'early childhood longitudinal study',\n 'survey of earned doctorates',\n 'national education longitudinal study',\n 'rural-urban continuum codes',\n 'sea, lake, and overland surges from hurricanes',\n 'baccalaureate and beyond',\n 'beginning postsecondary students',\n 'education longitudinal study',\n 'beginning postsecondary student']"
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 获取label，模拟预测用。\n",
    "titles = [x.lower() for x in set(train_df['dataset_title'].unique()).union(set(train_df['dataset_label'].unique()))]"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "outputs": [],
   "source": [
    "# 转小写\n",
    "# kaggle主页上有说明\n",
    "def clean_text(txt):\n",
    "    return re.sub('[^A-Za-z0-9]+', ' ', str(txt).lower()).strip()"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "outputs": [
    {
     "data": {
      "text/plain": "                                     Id  \\\n0  2100032a-7c33-4bff-97ef-690822c43466   \n1  2f392438-e215-4169-bebf-21ac4ff253e1   \n2  3f316b38-1a24-45a9-8d8c-4e05a42257c6   \n3  8e6996b4-ca08-4c0b-bed2-aaf07a4c6a60   \n\n                                    PredictionString  \n0  adni|alzheimer s disease neuroimaging initiati...  \n1  nces common core of data|trends in internation...  \n2  slosh model|sea lake and overland surges from ...  \n3                        rural urban continuum codes  ",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Id</th>\n      <th>PredictionString</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>2100032a-7c33-4bff-97ef-690822c43466</td>\n      <td>adni|alzheimer s disease neuroimaging initiati...</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2f392438-e215-4169-bebf-21ac4ff253e1</td>\n      <td>nces common core of data|trends in internation...</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>3f316b38-1a24-45a9-8d8c-4e05a42257c6</td>\n      <td>slosh model|sea lake and overland surges from ...</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>8e6996b4-ca08-4c0b-bed2-aaf07a4c6a60</td>\n      <td>rural urban continuum codes</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "submission_df = pd.read_csv(\"kaggle/input/coleridgeinitiative-show-us-the-data/sample_submission.csv\")\n",
    "\n",
    "#matching the string\n",
    "labels = []\n",
    "# 模拟模型预测label\n",
    "for index in submission_df['Id']:\n",
    "    pub_text = test[test['Id'] == index].text.str.cat(sep = '\\n').lower()\n",
    "    #print(pub_text)\n",
    "    label = []\n",
    "    for data_title in titles:\n",
    "        if data_title in pub_text:\n",
    "            label.append(clean_text(data_title))\n",
    "\n",
    "\n",
    "    labels.append(\"|\".join(label))\n",
    "\n",
    "# 根据提交文件要求写入table\n",
    "submission_df['PredictionString'] = labels\n",
    "submission_df"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "outputs": [],
   "source": [
    "# 写入提交文件\n",
    "# submission_df.to_csv('submission.csv', index = False)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
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